Mission: Our long-term goal is to understanding how genes and environment interact to influence risk of environmentally induced disease. To this end we are engaged in "Environmental Genomics." This encompasses: 1) Discovery of candidate environmental response genes and polymorphisms in these genes; 2) functional characterization of genetic and phenotypic variation in these genes, and; 3) the analysis in population studies of environmental disease susceptibility associated with functional polymorphisms, acquired susceptibility factors and exposures; and the interactions between these factors. Eventually we hope these genomic approaches will help us to develop assays using genotype, gene expression, and other biomarkers of exposure and effect, that will be predictive of future risk. This information will allow us to more carefully determine the bounds of human variability in risk assessment and will be useful in developing prevention strategies to reduce disease incidence. Identifying polymorphisms in exposure-induced genes. We developed bioinformatics methods to categorize SNPs in specific DNA sequence motifs. In our bioinformatics project we use these methods to identify polymorphic promoter response elements in candidate environmental response genes (see p53 project). If practical, the effects of these SNPs are then evaluated in functional assays. In addition, we are examining the relationship between genetic variation and variation in exposure-induced gene expression profiles. We have established proof of principal by comparing the response to exposure in cell lines that carry known polymorphisms in various environmental response genes. This discovery project produces techniques, descriptive genomic information and leads that are then validated and verified using functional genomics approaches and population studies. The p53 tumor suppressor protein is a master regulatory transcription factor that coordinates cellular responses to DNA damage and other sources of cellular stress. Besides mutations in p53, or in proteins involved in the p53 response pathway, genetic variation in promoter response elements (REs) of individual p53 target genes are expected to alter biological responses to stress. p53 project aims: 1) Develop bioinformatic tools that identifies functional SNPs in p53 transcription factor binding sites 2)functionally assess candidate SNPs in molecular and cellular assays under p53-control in yeast and mammalian cells. Computational discovery and functional validation of polymorphisms in the ARE/NRF2 response pathway Project Summary: The antioxidant response element (ARE) is a cis-acting enhancer sequence found in the promoter region of many genes encoding anti-oxidative and Phase II detoxification enzymes. In response to oxidative stress, the transcription factor NRF2 binds to AREs, mediating transcriptional activation of responsive genes and thereby modulating in vivo defense mechanisms against oxidative damage. Although studies identifying new genes in the ARE/NRF2 pathway have given insights into potential mechanisms of environmentally induced human disease, little is known about sequence variants that affect gene expression levels or that have functional phenotypic impact on exposure response. The overall objective of our proposal is to identify sets of single nucleotide polymorphism (SNP) allele pairs that modulate expression of ARE/NRF2-responsive genes in human tissues (i.e. one allele weakens or abolishes the ARE/NRF2-dependent response of the adjacent gene). Aims: 1) Computationally evaluate ~10.5 million human single nucleotide polymorphisms (SNPs) to identify polymorphisms in ARE/NRF2 responsive genes; 2) Screen and prioritize the top candidates after analyzing available functional data, validation of genotype frequency, and evaluating expression in relevant tissues; 3) Characterize functional differences (i.e. luciferase, chromatin immunoprecipitation) between polymorphic alleles in NRF2-responsive genes identified in Aims 1 and 2. Significance: The ARE/NRF2 response element SNPs identified here may be risk factors for developing oxidant-induced injury and may be predictive of clinical outcome following injury. This knowledge will be useful for identifying high-risk individuals and for developing novel prevention and treatment strategies